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About LabMol

Our research group is focused on designing of new drug candidates for infectious diseases such as Chagas disease, schistosomiasis, leishmaniasis, malaria and tuberculosis, as well as for cancer. Another important goal of our group is the development of predictive models for pharmacokinetics and toxicity properties. The work developed by our group has resulted in publications in international indexed journals, abstracts, dissertations and awards in national and international meetings of Medicinal and Computational Chemistry area.

Computer-Assisted Drug Design for Neglected Tropical Diseases

We aim to design and develop new chemical entities for the treatment of neglected tropical diseases, such as Dengue, Malaria, Schistosomiasis, Leishmaniasis, Chagas disease, among others, using structure-based drug design (SBDD) and ligand-based drug design (LBDD) strategies for the identification of selective inhibitors of target enzymes, by the combination of experimental and computational approaches.

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Carolina Andrade

Professor and Lab Head

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Flávia Silva

Ph.D. student

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Vinicius Alves

Ph.D. student

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Rodolpho Braga

Researcher at DNDi - USP

Development of In Silico Tools for Predicting Pharmacokinetics Properties

Optimization of pharmacokinetics properties (ADME: absorption, distribution, metabolism and excretion) at early stages of drug development has become an essential task to enhance the success rate of new drugs. We are working to overcome or reduce ADME late-stage failures by developing in silico tools or platforms to predict and optimize some of those properties, such as metabolism, Caco-2 cell permeability, blood-brain barrier penetration (BBBP), water solubility, among others, aiming to help the selection of compounds for clinical development.

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Carolina Andrade

Professor and Lab Head

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Flávia Silva

Ph.D. student

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Vinicius Alves

Ph.D. student

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Rodolpho Braga

Researcher at DNDi - USP

Computational Toxicology

We aim to apply computer methods to predict adverse effects of chemicals on human health and the environment, as well as to understand the mechanisms underlying the adverse outcome pathway of toxicological endpoints. The application of high-powered computing techniques allows us to manage and detect patterns and interactions in large biological and chemical data sets that helps to select potentially safer compounds to continue on the drug discovery pipeline.

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Carolina Andrade

Professor and Lab Head

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Eugene Muratov

Professor at UNC at Chapel Hill, USA

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Vinicius Alves

Ph.D. student

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Rodolpho Braga

Researcher at DNDi - USP

OpenZika

The OpenZika project on World Community Grid aims to identify drug candidates to treat the Zika virus in someone who has been infected. The project will target proteins that the Zika virus likely uses to survive and spread in the body based on what is known from diseases such as dengue virus and yellow fever. In order to develop an anti-Zika drug, researchers need to identify which of millions of chemical compounds might be effective at interfering with these key proteins. The effectiveness of each compound will be tested in virtual experiments, called “docking calculations,” performed on World Community Grid volunteers’ computers and Android devices. These calculations will help researchers focus on the most likely compounds that may eventually lead to an antiviral medicine.

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Carolina Andrade

Professor at Universidade Federal de Goiás and LabMol Head

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Alexander Perryman

Research Teaching Specialist, Rutgers University

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Melina Mottin

Research Associate at LabMol

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Sean Ekins

CEO, Collaborations Pharmaceuticals, Inc.

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Rodolpho Braga

Researcher at DNDi - USP

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Roosevelt Silva

Professor, Universidade Federal de Goiás